Build your First AI Agent with MCP from Scratch | Google ADK, Python, MCP Inspector (Hands-On)

This hands-on tutorial demonstrates how to build a real AI customer-support agent using the Model Context Protocol (MCP), Google ADK, and Python. The session covers the fundamentals of how AI agents and MCP work together, providing practical implementation guidance. The MCP Inspector tool is used throughout to debug and understand the agent's behavior in real-time.

Key Points

• •MCP (Model Context Protocol) enables AI agents to interact with external tools and data sources through a standardized interface
• •Google ADK provides the framework and utilities needed to build production-ready AI agents
• •Python is used as the primary language for implementing agent logic and MCP server connections
• •MCP Inspector is essential for debugging agent behavior and understanding tool invocations
• •Customer-support agents require integration with multiple data sources and tools for effective operation
• •Agents follow a request-response cycle where they analyze user input, select appropriate tools, and execute actions
• •Tool definitions in MCP must clearly specify inputs, outputs, and expected behavior for proper agent utilization
• •Testing and iteration using MCP Inspector helps validate agent responses before production deployment

Workflow Diagram

Concepts